Automatical Scaling of Es Layer Echoes on Ionograms ormalsize

Sporadic E (Es) and its echoes have a big impact on the measurement and inversion of the F-layer echoes, and it also affect the short-wave communication. This paper proposed a method based on decision tree algorithm to automatically identify Es layer and its echoes on ionograms. First, the ionogram was preprocessed by adaptive binarization and median filtering algorithms, the effective Es echo region was extracted from ionograms. Moreover, with characteristics of Es layer echoes on ionograms, the features were selected by image projection method. The features of Es layer on the projection values of the virtual height and the occurrence time of the Es layer were used as input of the decision tree algorithm to construct the decision tree. And manually labeled tag on ionograms and compare it with the output of the decision tree algorithm. Then trained to get closer to the results of manual labeled. In the present study, ionograms recorded at Pu'er Station (22.7°N, 101.5°E) in Yunnan province were used to construct the decision tree.the ionograms of Yunnan Pu'er Station (22.7°N, 101.5°E) and Sichuan Leshan Station (29.5°N, 103.7°E) were used as test sets respectively. The method was tested and verified. That method has high accuracy for the identification of Es two-hop echoes in both Pu'er and Leshan stations, reaching 84.2% and 82.8% respectively.